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Trust and risk in consumer acceptance of e-services

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An Erratum to this article was published on 21 December 2015

Abstract

Consumers’ risk perception and trust are considered among the most important psychological states that influence online behavior. Despite the number of empirical studies that have explored the effects of trust and risk perceptions on consumer acceptance of e-services, the field remains fragmented and the posited research models are contradictory. To address this problem, we examined how trust and risk influence consumer acceptance of e-services through a meta-analysis of 67 studies, followed by tests of competing causal models. The findings confirm that trust and risk are important to e-services acceptance but that trust has a stronger effect size. We found that certain effect sizes were moderated by factors such as the consumer population under study, the type of e-service, and the object of trust under consideration. The data from the meta-analysis best supports the causal logic that positions trust as antecedent to risk perceptions. Risk partially mediates the effects of trust on acceptance.

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Notes

  1. The use of two coders helps to increase coding reliability and can provide a check on the coding and effect size calculations.

  2. \( Z = \left( {Z_{y,a} - Z_{y,b} } \right)\sqrt {\frac{N - 3}{{2\left( {1 - r_{ab} } \right)h^{{\prime }} }}} \), where Zy,a and Zy,b are Fisher’s Z-transformations, N is the sample size, h is \( {{(1 - f\bar{r}^{2} )} \mathord{\left/ {\vphantom {{(1 - f\bar{r}^{2} )} {(1 - r^{2} ),\;f\;{\text{is}}\;\frac{{1 - r_{a,b} }}{{2(1 - \bar{r}^{2} )}},}}} \right. \kern-0pt} {(1 - r^{2} ),\;f\;{\text{is}}\;\frac{{1 - r_{a,b} }}{{2(1 - \bar{r}^{2} )}},}} \) and \( \bar{r}^{2} \) is \( \frac{{x_{y,a}^{2} + x_{y,b}^{2} }}{2} \) [71]. Given the number of correlations (K) between TR-ATT (K = 21) and PR-ATT (K = 20), TR-BI (K = 71) and PR-BI (K = 68) are different. To examine whether trust has a significantly stronger effect on attitude, we used K = 20 as the previous formula’s N. For the effects on behavior intention, we adopted K = 68 as the formula’s N.

  3. \( {\text{Harmonic mean = N}}/( 1/{\text{a}}_{ 1} + 1/{\text{a}}_{ 2} + 1/{\text{a}}_{ 3} + 1/{\text{a}}_{ 4} + \cdots + 1/{\text{a}}_{\text{n}} ) \).

References

*References marked with an asterisk refer to studies included in the MASEM analysis

  1. * Abadi, H. R. D., Hafshejani, S. N. A., & Zadeh, F. K. (2011). Considering factors that affect users’ online purchase intentions with using structural equation modelling. Interdisciplinary Journal of Contemporary Research in Business, 3(8), 463–471.

  2. * AI-Jabri, I. M. (2015). The intention to use mobile banking: Further evidence from Saudi Arabia. South African Business Management, 46(1), 23–34.

  3. * Aloudat, A., Michael, K., Chen, X., & Al-Dei, M. (2014). Social acceptance of location-based mobile government services for emergency management. Telematics and Informatics, 31, 153–171.

  4. Ba, S., & Pavlou, P. A. (2002). Evidence of the effect of trust building technology in electronic markets, no. price premiums and buyer behavior. MIS Quarterly, 26(3), 243–268.

    Article  Google Scholar 

  5. * Bansal, G., Zahedi, F. M., & Gefen, D. (2010). The impact of personal dispositions on information sensitivity, privacy concern and trust in disclosing health information online. Decision Support Systems, 49, 138–150.

  6. Bart, Y., Shankar, V., Sultan, F., & Urban, G. L. (2005). Are the drivers and role of online trust the same for all web sites and consumers? A large-scale exploratory empirical study. Journal of Marketing, 69(4), 133–152.

    Article  Google Scholar 

  7. Bélanger, F., & Carter, L. (2008). Trust and risk in E-Government adoption. Journal of Strategic Information Systems, 17, 165–176.

    Article  Google Scholar 

  8. Bhattacherjee, A. (2002). Individual trust in online firms: Scale development and initial test. Journal of Management Information Systems, 19(1), 211–241.

    Google Scholar 

  9. * Bianchi, C., & Andrews, L. (2012). Risk, trust, and consumer online purchasing behaviour: A Chilean perspective. International Marketing Review, 29(3), 253–276.

  10. Bokhari, R. H. (2005). The relationship between system usage and user satisfaction: A meta-analysis. The Journal of Enterprise Information Management, 18(2), 211–234.

    Article  Google Scholar 

  11. * Chandra, S., Srivastava, S. C., & Theng, Y. L. (2010). Evaluating the role of trust in consumer adoption of mobile payment systems: An empirical analysis. Communications of the Association for Information Systems, 27, 561–588.

  12. Chiu, C. M., Hsu, M. H., Lai, H., & Chang, C. M. (2012). Re-examining the influence of trust on online repeat purchase intention: The moderating role of habit and its antecedents. Decision Support Systems, 53, 835–845.

    Article  Google Scholar 

  13. * Cho, V. (2006). A study of the roles of trusts and risks in information-oriented online legal services using an integrated model. Information & Management, 43, 502–520.

  14. Compeau, D., Marcolin, B., Kelley, H., & Higgins, C. (2012). Research commentary generalizability of information systems research using student subjects—A reflection on our practices and recommendations for future research. Information Systems Research, 23(4), 1093–1109.

    Article  Google Scholar 

  15. * Corbitt, B. J., Thanasankit, T., & Yi, H. (2003). Trust and e-commerce: A study of consumer perceptions. Electronic Commerce Research and Applications, 2, 203–215.

  16. Corritore, C. L., Kracher, B., & Wiedenbeck, S. (2003). On-line trust: Concepts, evolving themes, a model. International Journal of Human-Computer Studies, 58, 737–758.

    Article  Google Scholar 

  17. * Curry, P. (2011). Consumer risk: The importance of privacy and security while connected to Wi-Fi hotspots: does location matter? In Proceedings of the 2011 AMCIS.

  18. * D’Alessandro, S., Girardi, A., & Tiangsoongnern, L. (2012). Perceived risk and trust as antecedents of online purchasing behavior in the USA gemstone industry. Asia Pacific Journal of Marketing and Logistics, 24(3), 433–460.

  19. de Ruyter, K., Wetzels, M., & Kleijnen, M. (2001). Customer adoption of e-service: An experimental study. International Journal of Service Industry Management, 12(2), 184–207.

    Article  Google Scholar 

  20. * Dinev, T., & Hart, P. (2006). An Extended privacy calculus model for e-commerce transactions. Information Systems Research, 17(1), 61–80.

  21. * Dinev, T., Bellotto, M., Hart, P., Russo, V., Serra, I., & Colautti, C. (2006). Privacy calculus model in e-commerce—A study of Italy and the United States. European Journal of Information Systems, 15, 389–402.

  22. Doney, P. M., Cannon, J. P., & Mullen, M. R. (1998). Understanding the influence of national culture on the development of trust. The Academy of Management Review, 23(3), 601–620.

    Google Scholar 

  23. Egea, J. M. O., & Gonzalez, M. V. R. (2011). Explaining physicians’ acceptance of EHCR systems: An extension of TAM with trust and risk factors. Computers in Human Behavior, 27, 319–332.

    Article  Google Scholar 

  24. * Faqih, K. M. S. (2011). Integrating perceived risk and trust with technology acceptance model: An empirical assessment of customers’ acceptance of online shopping in Jordan. In Proceedings of the 2011 international conference on research and innovation in information systems, Vol. ICRIIS.

  25. Garbarino, E., & Strahilevitz, M. (2004). Gender differences in the perceived risk of buying online and the effects of receiving a site recommendation. Journal of Business Research, 57, 768–775.

    Article  Google Scholar 

  26. Gefen, D. (2002). Reflections on the dimensions of trust and trustworthiness among online consumers. ACM Sigmis Database, 33(3), 38–53.

    Article  Google Scholar 

  27. * Gefen, D. (2002). Customer loyalty in e-commerce. Journal of Association for Information Systems, 3, 27–51.

  28. Gefen, D., & Heart, T. (2006). On the need to include national culture as a central issue in e-commerce trust beliefs. Journal of Global Information Management, 14(4), 1–30.

    Article  Google Scholar 

  29. * Gefen, D., & Pavlou, P. (2006). The moderating role of perceived regulatory effectiveness of online marketplaces on the role of trust and risk on transaction intentions. In Proceedings of the 2006 ICIS (pp. 1313–1330).

  30. Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51–90.

    Google Scholar 

  31. Gefen, D., V. Rao, & N. Tractinsky. (2003). Conceptualization of trust, risk and their relationship in electronic commerce: The need for clarifications. In Proceedings of the 36th Hawaii international conference on IS.

  32. Gefen, D., Rose, G. M., Warkentin, M., & Pavlou, P. (2005). Cultural diversity and trust in IT adoption: A comparison of USA and South African e-voters. Journal of Global Information Management, 13(1), 54–78.

    Article  Google Scholar 

  33. * Gurung, A. (2006). Empirical investigation of the relationship of privacy, security and trust with behavioural intention to transact in e-commerce, For the Degree of Doctor of Philosophy, the University of Texas at Arlington

  34. Harridge-March, S. (2006). Can the building of trust overcome consumer perceived risk online? Marketing Intelligence & Planning, 24(7), 746–761.

    Article  Google Scholar 

  35. He, J., & King, W. (2008). The role of user participation in information systems development: Implications from a meta-analysis. Journal of Management Information Systems, 25(1), 301–331.

    Article  Google Scholar 

  36. Hedges, L., & Olkin, I. (1985). Statistical methods for meta-analysis. Orlando, FL: Academic Press.

    Google Scholar 

  37. Holbert, R. L., & Stephenson, M. T. (2002). Structural equation modeling in the communication sciences, 1995–2000. Human Communication Research, 28(4), 531–551.

    Google Scholar 

  38. * Hong, I. B. (2015). Understanding the consumer’s online merchant selection process: The roles of product involvement, perceived risk, and trust expectation. International Journal of Information Management, 35, 322–336.

  39. * Horst, M., Kuttschreuter, M., & Gutteling, J. M. (2007). Perceived usefulness, personal experiences, risk perception and trust as determinants of adoption of e-government services in The Netherlands. Computer in Human Behavior, 23, 1838–1852.

  40. Hunter, J. E., & Schmidt, F. L. (2004). Methods of meta-analysis correcting error and bias in research findings. London: New Delhi, SAGE Publicantions.

    Google Scholar 

  41. * Hussein, R., Mohamed, N., Ahlan, A. R., & Mahumd, M. (2011). E-Government application: An integrated model on G2C adoption of online tax. Transforming Government: People, Process and Policy, 5(3), 225–248.

  42. * Izquierdo-Yusta, A., & Galderon-Monge, E. (2011). Internet as a distribution channel: Empirical evidence from the service sector and managerial opportunities. Journal of Internet Commerce, 10, 106–127.

  43. * Jarvenpaa, S. L., Tracinsky, N., & Vitale, M. (2000). Consumer trust in an internet store. Information Technology and Management, 1(1), 45–71.

  44. Joseph, D., Ng, K. Y., Koh, C., & Ang, S. (2007). Turnover of information technology professionals: A narrative review, meta-analytic structural equation modeling, and model development. MIS Quarterly, 31(3), 547–577.

    Google Scholar 

  45. * Katos, V. (2012). An integrated model for online transactions: Illuminating the black box. Information Management and Computer Security, 20(3), 184–206.

  46. * Kehr, F., Kowatsch, T., Wentzel, D., & Fleisch, E. (2015). Blissfully ignorant: The effects of general privacy concerns, general institutional trust, and affect in the privacy calculus. Information Systems Journal, 25(6), 607–635.

  47. * Kehr, F., Wentzel, D., Kowatsch, R., & Fleisch, E. (2015). Rethinking privacy decisions: Pre-existing attitudes, pre-existing emotional states, and a situational privacy calculus. In Proceedings of twenty-third European conference on information systems.

  48. Kerler, W. A., & Killough, L. N. (2009). The effects of satisfaction with a client’s management during a prior audit engagement, trust, and moral reasoning. Journal of Business Ethics, 85, 109–136.

    Article  Google Scholar 

  49. * Kesharwani, A., & Bisht, S. S. (2012). The impact of trust and perceived risk on internet banking adoption in India. International Journal of Bank Marketing, 30(4), 303–322.

  50. * Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision Support Systems, 44(2), 544–564.

  51. * Kim, D. J., Ferrin, D. L., & Rao, H. R. (2009). Trust and satisfaction, two stepping stones for successful e-commerce relationships: A longitudinal exploration. Information Systems Research, 20(2), 237–257.

  52. * Kimery, K., & McCord, M. (2002). Third-party assurances: The road to trust in online retailing. In Proceedings of the 35th Hawaii international conference on system sciences.

  53. * Kimery, L. M., & McCord, M. (2002). Third-party assurances: Mapping the road to trust in e-retailing. Journal of Information Technology Theory and Application, 4(2), 63–82.

  54. King, W. R., & He, J. (2005). Understanding the role and methods of meta-analysis in IS research. Communications of the Association for Information Systems, 16, 665–686.

    Google Scholar 

  55. * Krasnova, H., Spiekermann, S., Koroleva, K., & Hildebrand, T. (2010). Online social networks: Why we disclose. Journal of Information Technology, 25, 109–125.

  56. * Lee, M. C. (2009). Predicting and explaining the adoption of online trading: An empirical study in Taiwan. Decision Support Systems, 47, 133–142.

  57. Lei, P. W., & Wu, Q. (2007). Introduction to structural equation modeling: Issues and practical considerations. Educational Measurement: Issues and Practice, 26(3), 33–43.

    Article  Google Scholar 

  58. * Li, R., Kim, J. J., & Park, J. S. (2007). The effects of internet shoppers’ trust on their purchasing intention in China. Journal of Information Systems and Technology Management, 4(3), 269–286.

  59. * Li, H., Ye, Q., Law, R., & Wang, Z. (2010). A purchasing-intention model in C2C e-commerce of China: The role of perceived risk, trust, perceived benefit and their antecedents. In Proceedings of the 12th international conference on electronic commerce (pp. 101–109).

  60. * Li, H., Gupta, A., Zhang, J., & Sarathy, R. (2014). Examining the decision to use standalone personal health record systems as a trust-enabled fair social contract. Decision Support Systems, 57, 376–386.

  61. * Liao, C., Liu, C. C., & Chen, K. (2011). Examining the impact privacy, trust and risk perceptions beyond monetary transactions: An integrated model. Electronic Commerce Research and Applications, 10, 702–715.

  62. * Lim, K. S., Lim, J. S., & Heinrichs, J. H. (2008). Testing and integrated model of e-shopping web site usage. Journal of Internet Commerce, 7(3), 291–312.

  63. * Lo, J. (2010). Privacy concern, locus of control, and salience in a trust-risk model of information disclosure on social networking sites. In Proceedings of the 2010 AMCIS (pp. 1–12).

  64. * Lorenzo-Romero, C. L., Constantinides, E., & Alarcón-del-Amo, M. C. (2011). Consumer adoption of social networking sites: Implications for theory and practice. Journal of Research in Interactive Marketing, 5(2/3), 170–188.

  65. * Lu, Y., Yang, S., Chau, P. Y. K., & Cao, Y. (2011). Dynamics between the trust transfer process and intention to use mobile payment services: A cross-environment perspective. Information & Management, 48, 393–403.

  66. * Luo, X., Li, H., Zhang, J., & Shim, J. P. (2010). Examining multi-dimensional trust and multi-faceted risk in initial acceptance of emerging technologies: an empirical study of mobile banking services. Decision Support Systems, 49, 222–234.

  67. * Malhotra, N. K., Kim, S. S., & Agarwal, J. (2004). Internet users’ information privacy concerns, Vol. IUIPC: The construct, the scale, and a causal model. Information Systems Research, 15(4), 336–355.

  68. * Martínez-López, F. J., Esteban-Millat, I., Cabal, C. C., & Gengler, C. (2015). Psychological factors explaining consumer adoption of an e-vendor’s recommender. Industrial Management & Data Systems, 115(2), 284–310.

  69. McAllister, D. J. (1995). Affect-and cognition-based trust as foundations for interpersonal cooperation in organizations. Academy of Management Journal, 38(1), 24–59.

    Article  Google Scholar 

  70. McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). Developing and validating trust measures for e-commerce: An integrative typology. Information Systems Research, 13(3), 334–359.

    Article  Google Scholar 

  71. Meng, X., Rosenthal, R., & Rubin, D. (1992). Comparing correlated correlation coefficients. Psychological Bulletin, 111(1), 172–175.

    Article  Google Scholar 

  72. * Morosan, C., & DeFranco, A. (2015). Disclosing personal information via hotel apps: A privacy calculus perspective. International Journal of Hospitality Management, 47, 120–130.

  73. Mou, J., & Cohen, J. F. (2014). Trust, risk and perceived usefulness in consumer acceptance of online health services. In 25th Australasian conference on information systems, Auckland.

  74. * Nicolaou, A. I., & McKnight, D. H. (2006). Perceived information quality in data exchanges: Effects on risk, trust, and intention to use. Information Systems Research, 17(4), 332–351.

  75. Parboteeah, D. V., Valacich, J. S., & Wells, J. D. (2009). The influence of website characteristics on a consumer’s urge to buy impulsively. Information Systems Research, 20(1), 60–78.

    Article  Google Scholar 

  76. Park, J. K., Gunn, F., & Han, S. L. (2012). Multidimensional trust building in e-retailing: Cross-cultural differences in trust formation and implications for perceived risk. Journal of Retailing and Consumer Services, 19, 304–312.

    Article  Google Scholar 

  77. * Pavlou, P. A. (2001). Integrating trust in electronic commerce with the technology acceptance model: Model development and validation. In Proceedings of the 2001 AMCIS (pp. 816–822).

  78. * Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 7(3), 101–134.

  79. Pavlou, P. A., & Gefen, D. (2002). Building effective online marketplaces with institution-based trust. In Proceedings of the twenty-third international conference on information systems (pp. 667–675).

  80. * Pavlou, P. A., & Gefen, D. (2004). Building effective online marketplaces with institution-based trust. Information Systems Research, 15(1), 37–59.

  81. * Pavlou, P. A., & Gefen, D. (2005). Psychological contract violation in online marketplaces: Antecedents, consequences, and moderating role. Information Systems Research, 16(4), 372–399.

  82. * Phonthanukitithaworn, C., Sellitto, C., & Fong, M. (2015). User intentions to adopt mobile payment services: A study of early adopters in Thailand. Journal of Internet Banking and Commerce, 20(1), 1–29.

  83. Ribbink, D., van Riel, A. C. R., Liljander, V., & Streukens, S. (2004). Comfort your online customer: Quality, trust and loyalty on the internet. Managing Service Quality, 14(6), 446–456.

    Article  Google Scholar 

  84. Rosenthal, R. (1979). The ‘File Drawer’ problem and tolerance for null results. Psychological Bulletin, 86, 638–641.

    Article  Google Scholar 

  85. Rust, R. T., & Kannan, P. K. (2003). E-service: A new paradigm for business in the electronic environment. Communications of the ACM, 36(6), 37–42.

    Google Scholar 

  86. * Schaupp, L. C., Carter, L., & McBride, M. E. (2010). E-file adoption: A study of U.S. taxpayers’ intentions. Computers in Human Behavior, 26, 636–644.

  87. Schepers, J., & Wetzels, M. (2007). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Information & Management, 44, 90–103.

    Article  Google Scholar 

  88. * Shin, D. (2008). Understanding purchasing behaviors in a virtual economy: Consumer behavior involving virtual currency in Web 2.0 communities. Interacting with Computers, 20, 433–446.

  89. Shin, D. (2010). The effects of trust, security and privacy in social networking: A security-based approach to understand the pattern of adoption. Interacting with Computers, 22(5), 428–438.

    Article  Google Scholar 

  90. * Shin, D. (2013). User experience in social commerce: In friends we trust. Behavior and Information Technology, 32(1), 52–67.

  91. Shin, D. (2015). Quality of experience: Beyond the user experience of smart services. Total Quality Management, 26(8), 919–932.

    Article  Google Scholar 

  92. * Shukla, P. (2014). The impact of organizational efforts on consumer concerns in an online context. Information & Management, 51, 113–119.

  93. * Slyke, C. V., Shim, J. T., Johnson, R., & Jiang, J. (2006). Concern for information privacy and online consumer purchasing. Journal of Association for Information Systems, 7(6), 415–444.

  94. Song, H. L. (2010). Customer adoption of internet banking: An integration of TAM with trust, perceived risk, and quality. In Proceedings of 2010 international conference on multimedia information networking and security (pp. 264–268).

  95. Taleghani, M., Sharifi, A. S., & Gilaninia, S. (2011). The role of key factors in e-banking for new enterprise, vol. concepts and applications. Interdisciplinary Journal of Contemporary Research in Business, 3(3), 999–1007.

    Google Scholar 

  96. * Teo, T. S. H., & Liu, J. (2007). Consumer trust in e-commerce in the United States, Singapore and China. The International Journal of Management Science, 35, 22–38.

  97. Thatcher, J. B., Carter, M., Li, X., & Rong, G. (2013). A classification and investigation of trustees in B-to-C e-commerce: General vs. specific trust. Communications of the Association for Information Systems, 32, 107–134.

    Google Scholar 

  98. Van der Heijden, H., Verhagen, T., & Creemers, M. (2003). Understanding online purchase intentions: Contributions from technology and trust perspectives. European Journal of Information Systems, 12, 41–48.

    Article  Google Scholar 

  99. Verhagen, T., Meents, S., & Tan, Y. (2006). Perceived risk and trust associated with purchasing at electronic marketplaces. European Journal of Information Systems, 15, 542–555.

    Article  Google Scholar 

  100. Viswesvaran, C., & Ones, D. S. (1995). Theory testing: Combining psychometric meta-analysis and structural equations modelling. Personnel Psychology, 48, 865–885.

    Article  Google Scholar 

  101. Weber, E. U., & Hsee, C. (1998). Cross-cultural differences in risk perception, but cross-cultural similarities in attitudes towards perceived risk. Management Science, 44(9), 1205–1217.

    Article  Google Scholar 

  102. Wu, J., & Lederer, A. (2009). A meta-analysis of the role of environment-based voluntariness in information technology acceptance. MIS Quarterly, 33(2), 419–432.

    Google Scholar 

  103. * Wu, K., Vassileva, J., Noorian, Z., & Zhao, Y. (2015). How do you feel when you see a list of prices? The interplay among price dispersion, perceived risk and initial trust in Chinese C2C market. Journal of Retailing and Consumer Services, 25, 36–46.

  104. * Xu, H., Teo, H. H., Tan, B. (2005). Predicting the adoption of location-based services: The role of trust and perceived privacy risk. In Proceedings of international conference on information systems (pp. 897–910).

  105. * Xu, H., Wang, H., & Teo, H. H. (2005). Predicting the usage of P2P sharing software: The role of trust and perceived risk. In Proceedings of the 38th Hawaii international conference on system sciences.

  106. Yamagishi, T., & Yamagishi, M. (1994). Trust and commitment in the United States and Japan. Motivation and Emotion, 18(2), 129–166.

    Article  Google Scholar 

  107. * Yang, Q., Pang, C., Liu, L., Yen, D., & Tarn, T. M. (2015). Exploring consumer perceived risk and trust for online payments: An empirical study in China’s younger generation. Computers in Human Behavior, 50, 9–24.

  108. * Yao, C., & Liao, S. (2011). Measuring the antecedent effects of service cognition and internet shopping anxiety on consumer satisfaction with e-tailing service. Management and Marketing Challenges for the Knowledge Society, 6(1), 59–78.

  109. * Yi, M. Y., Yoon, J. J., Davis, J. M., & Lee, T. (2013). Untangling the antecedents of initial trust in web-based health information: The roles of argument quality, source expertise, and user perceptions of information quality and risk. Decision Support Systems, 55, 284–295.

  110. Yousafzai, S. Y., Pallister, J. G., & Foxall, G. R. (2003). A proposed model of e-trust for electronic banking. Technovation, 23, 847–860.

    Article  Google Scholar 

  111. Yousafzai, S. Y., Foxall, G. R., & Pallister, J. G. (2007). Technology acceptance: A meta-analysis of the TAM: Part 2. Journal of Modelling in Management, 2(3), 281–304.

    Article  Google Scholar 

  112. * Yousafzai, S. Y., Pallister, J. G., & Foxall, G. R. (2009). Multi-dimensional role of trust in internet banking adoption. The Service Industries Journal, 29(5), 591–605.

  113. * Zhang, M., & Yang, M.(2009). Exploring credit card adoption and usage model of college student. In Proceedings of the 1st international conference on information science and engineering (pp. 2923–2927)

  114. Zhang, L., Zhu, J., & Liu, Q. (2012). A meta-analysis of mobile commerce adoption and the moderating effect of culture. Computers in Human Behavior, 28, 1902–1911.

    Article  Google Scholar 

  115. * Zhou, T. (2011). The impact of privacy concern on user adoption of location-based services. Industrial Management and Data Systems, 111(2), 212–226.

  116. * Zhou, T. (2013). An empirical examination of user adoption of location-based services. Electronic Commerce Research, 13, 25–39.

  117. * Zhu, D. S., Lee, Z. C., & Neal, G. S. O. (2011). Mr. Risk! Please trust me: Trust antecedents that increase online consumer purchase intention. Journal of Internet Banking and Commerce, 16(3), 1–23.

  118. * Zimmer, J. C., Arsal, R. E., Al-Marzouq, M., & Grover, V. (2010). Investigating online information disclosure: Effects of information relevance, trust and risk. Information & Management, 47, 115–123.

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Acknowledgments

This paper was supported by Sungkyun Research Fund, Sungkyunkwan University.

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  1. Department of Interaction Science, Sungkyunkwan University, 25-2 Sungkyunkwan-ro, Jongro-gu, Seoul, 110-745, Korea

    Jian Mou & Dong-Hee Shin

  2. University of the Witwatersrand, Private Bag x3, WITS, Johannesburg, 2050, South Africa

    Jason F. Cohen

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An erratum to this article is available at http://dx.doi.org/10.1007/s10660-015-9210-7.

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Table 10 Studies Used in Meta-Analysis
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Mou, J., Shin, DH. & Cohen, J.F. Trust and risk in consumer acceptance of e-services. Electron Commer Res 17, 255–288 (2017). https://doi.org/10.1007/s10660-015-9205-4

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